LLM Digest

Story

arxiv_cs_lg · Sep 26, 2026 · paper

Source brief

Learning When to Recur: Token-Adaptive Recursion for Imbalanced Ophthalmic Domain Incremental Learning

arxiv.orgSep 26, 2026
original source linked

In brief

Domain incremental learning is essential for adapting ophthalmic deep learning models to sequential clinical domains while preserving diagnostic expertise. Existing domain incremental learning methods predominantly ad...

Feed lens

evaluation

Read the original at arxiv.org →Open in live feed Read that day’s brief

Learning When to Recur: Token-Adaptive Recursion for Imbalanced Ophthalmic Domain Incremental Learning

Earlier in this thread 4 items

A Domain Incremental Continual Learning Benchmark for ICU Time Series Model Transportability

MAGIC: Mixed-Granularity Agent Graphs via Incremental Construction with Dense-Reward Reinforcement Learning

Best practices guide for customizing Gemini models via Reinforcement Learning (RL)

iSDFT: Information-Proximal Self-Distillation for Continual Learning in LLMs